In Marbr987/lab4: A package for linear regression models

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

library(lab4)

Setup

To install the lab4 package, source it from GitHub with the command devtools::install_github("Marbr987/lab4").

Usage of linreg function

The linreg() function can be used to perform a linear regression. It takes two arguments, formula and data, where formula is the formula consisting of parameters of data used to perform the regression. The function returns an object of class linreg.
The following example illustrates the use of linreg() with the iris dataset, which is also included in this package.

# Crate an object of class linreg by calling the linreg function
linreg_obj <- linreg(formula = Petal.Length ~ Species, data = iris)
class(linreg_obj)

# The linreg object is a list containing the following elements
names(linreg_obj)

Usage of methods for linreg objects

The print() method prints out the call of the function and the coefficients of the linear regresion.

print(linreg_obj)

The plot() function provides the two plots shown in the example below. It returns the plots in a list of size two.

plot_list <- plot(linreg_obj)
print(plot_list[1])
print(plot_list[2])

The resid() method prints out the residuals of the linear regression.

head(resid(linreg_obj))

The pred() method prints out the target values predicted by the linear regression.

head(pred(linreg_obj))

The coef() method prints out the coefficients of the linear regression.

coef(linreg_obj)

The summary() method prints a summary of the linear regression as seen in the example below.

summary(linreg_obj)

Marbr987/lab4 documentation built on Dec. 17, 2021, 2:20 a.m.